Structural plasticity underlies experience-dependent functional plasticity of cortical circuits

The stabilization of new spines in the barrel cortex is enhanced after whisker trimming, but its relationship to experience-dependent plasticity is unclear. Here we show that in wild-type mice, whisker potentiation and spine stabilization are most pronounced for layer 5 neurons at the border between spared and deprived barrel columns. In homozygote alphaCaMKII-T286A mice, which lack experience-dependent potentiation of responses to spared whiskers, there is no increase in new spine stabilization at the border between barrel columns after whisker trimming. Our data provide a causal link between new spine synapses and plasticity of adult cortical circuits and suggest that alphaCaMKII autophosphorylation plays a role in the stabilization but not formation of new spines

Identification of a Brainstem Circuit Regulating Visual Cortical State in Parallel with Locomotion

SummarySensory processing is dependent upon behavioral state. In mice, locomotion is accompanied by changes in cortical state and enhanced visual responses. Although recent studies have begun to elucidate intrinsic cortical mechanisms underlying this effect, the neural circuits that initially couple locomotion to cortical processing are unknown. The mesencephalic locomotor region (MLR) has been shown to be capable of initiating running and is associated with the ascending reticular activating system. Here, we find that optogenetic stimulation of the MLR in awake, head-fixed mice can induce both locomotion and increases in the gain of cortical responses. MLR stimulation below the threshold for overt movement similarly changed cortical processing, revealing that MLR’s effects on cortex are dissociable from locomotion. Likewise, stimulation of MLR projections to the basal forebrain also enhanced cortical responses, suggesting a pathway linking the MLR to cortex. These studies demonstrate that the MLR regulates cortical state in parallel with locomotion

A Significant but Rather Mild Contribution of T286 Autophosphorylation to Ca2+/CaM-Stimulated CaMKII Activity

Autophosphorylation of the Ca(2+)/calmodulin (CaM)-dependent protein kinase II (CaMKII) at T286 generates partially Ca(2+)/CaM-independent "autonomous" activity, which is thought to be required for long-term potentiation (LTP), a form of synaptic plasticity thought to underlie learning and memory. A requirement for T286 autophosphorylation also for efficient Ca(2+)/CaM-stimulated CaMKII activity has been described, but remains controversial.In order to determine the contribution of T286 autophosphorylation to Ca(2+)/CaM-stimulated CaMKII activity, the activity of CaMKII wild type and its phosphorylation-incompetent T286A mutant was compared. As the absolute activity can vary between individual kinase preparations, the activity was measured in six different extracts for each kinase (expressed in HEK-293 cells). Consistent with measurements on purified kinase (from a baculovirus/Sf9 cell expression system), CaMKII T286A showed a mildly but significantly reduced rate of Ca(2+)/CaM-stimulated phosphorylation for two different peptide substrates (to ~75-84% of wild type). Additional slower CaMKII autophosphorylation at T305/306 inhibits stimulation by Ca(2+)/CaM, but occurs only minimally for CaMKII wild type during CaM-stimulated activity assays. Thus, we tested if the T286A mutant may show more extensive inhibitory autophosphorylation, which could explain its reduced stimulated activity. By contrast, inhibitory autophosphorylation was instead found to be even further reduced for the T286A mutant under our assay conditions. On a side note, the phospho-T305 antibody showed some basal background immuno-reactivity also with non-phosphorylated CaMKII, as indicated by T305/306A mutants.These results indicate that Ca(2+)/CaM-stimulated CaMKII activity is mildly (~1.2-1.3fold) further increased by additional T286 autophosphorylation, but that this autophosphorylation is not required for the major part of the stimulated activity. This indicates that the phenotype of CaMKII T286A mutant mice is indeed due to the lack of autonomous activity, as the T286A mutant showed no dramatic reduction in stimulated activity

Spine Calcium Transients Induced by Synaptically-Evoked Action Potentials Can Predict Synapse Location and Establish Synaptic Democracy

CA1 pyramidal neurons receive hundreds of synaptic inputs at different distances from the soma. Distance-dependent synaptic scaling enables distal and proximal synapses to influence the somatic membrane equally, a phenomenon called “synaptic democracy”. How this is established is unclear. The backpropagating action potential (BAP) is hypothesised to provide distance-dependent information to synapses, allowing synaptic strengths to scale accordingly. Experimental measurements show that a BAP evoked by current injection at the soma causes calcium currents in the apical shaft whose amplitudes decay with distance from the soma. However, in vivo action potentials are not induced by somatic current injection but by synaptic inputs along the dendrites, which creates a different excitable state of the dendrites. Due to technical limitations, it is not possible to study experimentally whether distance information can also be provided by synaptically-evoked BAPs. Therefore we adapted a realistic morphological and electrophysiological model to measure BAP-induced voltage and calcium signals in spines after Schaffer collateral synapse stimulation. We show that peak calcium concentration is highly correlated with soma-synapse distance under a number of physiologically-realistic suprathreshold stimulation regimes and for a range of dendritic morphologies. Peak calcium levels also predicted the attenuation of the EPSP across the dendritic tree. Furthermore, we show that peak calcium can be used to set up a synaptic democracy in a homeostatic manner, whereby synapses regulate their synaptic strength on the basis of the difference between peak calcium and a uniform target value. We conclude that information derived from synaptically-generated BAPs can indicate synapse location and can subsequently be utilised to implement a synaptic democracy

Thermoelectric generator (TEG) technologies and applications

2021 The Author(s). Nowadays humans are facing difficult issues, such as increasing power costs, environmental pollution and global warming. In order to reduce their consequences, scientists are concentrating on improving power generators focused on energy harvesting. Thermoelectric generators (TEGs) have demonstrated their capacity to transform thermal energy directly into electric power through the Seebeck effect. Due to the unique advantages they present, thermoelectric systems have emerged during the last decade as a promising alternative among other technologies for green power production. In this regard, thermoelectric device output prediction is important both for determining the future use of this new technology and for specifying the key design parameters of thermoelectric generators and systems. Moreover, TEGs are environmentally safe, work quietly as they do not include mechanical mechanisms or rotating elements and can be manufactured on a broad variety of substrates such as silicon, polymers and ceramics. In addition, TEGs are position-independent, have a long working life and are ideal for bulk and compact applications. Furthermore, Thermoelectric generators have been found as a viable solution for direct generation of electricity from waste heat in industrial processes. This paper presents in-depth analysis of TEGs, beginning with a comprehensive overview of their working principles such as the Seebeck effect, the Peltier effect, the Thomson effect and Joule heating with their applications, materials used, Figure of Merit, improvement techniques including different thermoelectric material arrangements and technologies used and substrate types. Moreover, performance simulation examples such as COMSOL Multiphysics and ANSYS-Computational Fluid Dynamics are investigated

Neuron addition and loss in the song system: regulation and function

Neurons continue to be produced and replaced throughout life in songbirds. Proliferation in the walls of the lateral ventricles gives rise to neurons that migrate long distances to populate many diverse telencephalic regions, including nuclei dedicated to the perception and production of song, a learned behavior. Many projection neurons are incorporated into the efferent motor pathway for song control. Replacement of these neurons is regulated, in part, by neuron death. Underlying mechanisms include gonadal steroids and BDNF, but are likely to involve other trophic factors as well. The functional significance of neuronal replacement remains unclear. However, recent experiments suggest a link between cell turnover and one or more specific attributes of song learning and production. Several hypotheses are critically examined, including the possibility that neuronal replacement provides motor flexibility to allow for error correction-a capacity needed for juvenile and adult song learning, but also likely to be important for the maintenance of song stereotypy. We highlight important gaps in our knowledge and discuss future directions that may bring us closer to solving the riddle of why neurons are produced and replaced in adulthood

What do reinforcement learning models measure? Interpreting model parameters in cognition and neuroscience

Reinforcement learning (RL) is a concept that has been invaluable to fields including machine learning, neuroscience, and cognitive science. However, what RL entails differs between fields, leading to difficulties when interpreting and translating findings. After laying out these differences, this paper focuses on cognitive (neuro)science to discuss how we as a field might overinterpret RL modeling results. We too often assume — implicitly — that modeling results generalize between tasks, models, and participant populations, despite negative empirical evidence for this assumption. We also often assume that parameters measure specific, unique (neuro)cognitive processes, a concept we call interpretability, when evidence suggests that they capture different functions across studies and tasks. We conclude that future computational research needs to pay increased attention to implicit assumptions when using RL models, and suggest that a more systematic understanding of contextual factors will help address issues and improve the ability of RL to explain brain and behavior